Search

Previous papers in this series have presented a conceptual model of the individual decision to telecommute and explored relationships among constraints, preference, and choice. A related paper has developed a binary model of the preference for home-based telecom- muting. Noting that there is a wide gap between preferring to telecommute (88% of the sample) and actually telecommuting (13%), this paper develops binary logit models of role- commuting adoption. Two approaches to dealing with constraints are compared: incorporating them directly into the utility function, and using them to define the choice set. Models using the first approach appear to be statistically superior in this analysis, explaining 63-64% of the information in the data. Variables significant to choice include those relating to work and travel drives, and awareness, manager support, job suitability, technology, and discipline constraints. The best model was used to analyze the impact of relaxing three key constraints on the 355 people in the sample for whom telecommuting was previously identified to be a Preferred Impossible Alternative. When unawareness, lack of manager support, and job unsuitability constraints are relaxed, 28% of the people in the PIA category would be expected to adopt telecommuting. The importance of behavioral models to accurately forecasting telecommuting adoption is emphasized and is suggested to have wider implications for predicting technology-based activity changes.

Binary structure function theory has been developed to model the reliability aspects of both physical and nonphysical systems. Each component and system assumes either one of two possible states, failure or work, and the notion reliability has been defined in a probabilistic way. There are, however, some important deficiencies that cannot be overcome without extending the state space of both components and systems and, hence, allowing more than two possible states. Although many authors developed and described several models that extend the binary model, some fundamental notions like state and state space are almost never discussed or described. In this paper, however, we introduce some new ideas about the notion state in reliability theory and we construct a general framework to describe the reliability aspects of multistate systems and their components.

In the present article, the dynamics of a fluid-saturated porous solid material is described by the general theory of porous media, which is defined as the classical theory of mixtures extended by the concept of volume fractions. The reader, who is interested in the various details of this approach is referred, e. g., to Bowen [1, 2], Ehlers [3] or de Boer et al. [4]. For simplicity and convenience, thermal effects as well as mass exchanges between the constituents are excluded from the following treatment. Based on this approach, the objective of the paper is to re-formulate and to solve the mechanical balance equations of a binary model, especially, of a binary model of incompressible constituents (elastic solid skeleton and viscous pore fluid). In particular, initial boundary-value problems of one-dimensional and two-dimensional dynamic consolidation problems are solved within the finite element method (FEM), thus delivering a successful alternative to the different numerical studies based on the well-known Biot approach; concerning the Biot approach, compare [5, 6, 7].

A new custom .nite element (FE) code based on the Binary Model is developed. The program is capable for investigation of the dynamic material properties of textile reinforced composites such as during impact. Therefore, the established formulation of the Binary Model for boundary value problems in Ref. [1,2,3] is enhanced to initial value problems. Regarding the investigation of the impact behavior, the program provides an apt .exibility in determination of boundary conditions. The calculations of di.erent models show the precision and reasonableness of the results from this FE program. The work done for this paper is partially sponsored by the German Research Community (DFG) in the context of the priority program (SPP) no. 1123.

High-magnification microlensing events provide an important channel to detect planets. Perturbations near the peak of a high-magnification event can be produced either by a planet or a binary companion. It is known that central perturbations induced by both types of companions can be generally distinguished due to the basically different magnification pattern around caustics. In this paper, we present a case of central perturbations for which it is difficult to distinguish the planetary and binary interpretations. The peak of a lensing light curve affected by this perturbation appears to be blunt and flat. For a planetary case, this perturbation occurs when the source trajectory passes the negative perturbation region behind the back end of an arrowhead-shaped central caustic. For a binary case, a similar perturbation occurs for a source trajectory passing through the negative perturbation region between two cusps of an astroid-shaped caustic. We demonstrate the degeneracy for 2 high-magnification events of OGLE-2011-BLG-0526 and OGLE-2011-BLG-0950/MOA-2011-BLG-336. For OGLE-2011-BLG-0526, the $\chi^2$ difference between the planetary and binary model is $\sim$ 3, implying that the degeneracy is very severe. For OGLE-2011-BLG-0950/MOA-2011-BLG-336, the stellar binary model is formally excluded with $\Delta \chi^2 \sim$ 105 and the planetary model is preferred. However, it is difficult to claim a planet discovery because systematic residuals of data from the planetary model are larger than the difference between the planetary and binary models. Considering that 2 events observed during a single season suffer from such a degeneracy, it is expected that central perturbations experiencing this type of degeneracy is common., Comment: 8 pages, 8 figures

Naïve Bayes is a simple and efficient classification algorithm which performs well on text classification, which is also known as text categorization. Many researches have been done to improve the performance of the naïve Bayes classifier by weighting the correlated terms, in order to relax the strong assumption of independence between terms. In this paper, we first introduce a new χ2 statistical data, denoted by Rw,c, which can measure positive term-class dependency accurately, and then propose a new weighted naïve Bayes classifier using Rw,c at the training phase. Experimental results with real data sets show that our weighted naïve Bayes classifier has much better performance than the basic naïve Bayes classifier in most cases.

In this chapter, we analyze how alternative organizations of information production interact with incentive provision. Some related questions were addressed in chapter 3. The main difference is that we now impose more structure on the choice sets and the player’s motivations, such that we are able to push the analysis quite a bit further.

The fragmentation-inactivation binary model of the fragmentation at the transition line between the “∞-cluster” phase and the “shattering” phase is applied for analyzing the nuclear multifragmentation data of ALADIN Collaboration for average charged-particle correlations in 600 MeV/μ gold induced reactions on various targets. A constant break-up kernel, independent of the sizes of the daughter fragments, is used. By adjusting the strength of the inactivation probability function to the correlation between the mean size of the largest cluster and the composed particle first moment, we find that the remaining charge correlation data is correctly reproduced by the fragmentation-inactivation binary model.

This paper reviews and extends earlier results on input/output based variable structure adaptive control algorithms and its binary (in the sense of Emelyanov) version. The latter was formulated only for the case of plants with relative degree one. Here a new controller is proposed for the general case of arbitrary relative degree. The new adaptive control scheme, termed binary model reference adaptive control (B–MRAC), is shown to have global exponential stability properties.

In this chapter we present some common models for analysis of system reliability. First we study the structural relations between a system and its components. Then methods for calculation of system reliability are studied, when the component reliabilities are known. Models for non-repairable and repairable systems are looked into. The components are assumed to be functioning/not functioning independently of each other, except in Section 3.6 where dependency is discussed.

In recent times, many organisations are failing in their attempt to achieve a world-class status through Total Productive Maintenance (TPM) due to various shortcomings. Hence, in our earlier study, a new framework for World-Class Maintenance Systems (WMS) was proposed to overcome some of these shortcomings. Organisations that are planning to adapt World-Class Manufacturing (WCM) practices such as TPM, WMS etc. require proper justification to convince the top management. Hence, in this paper, an application of a Multi-Attribute Decision-Making (MADM) model – namely, the Analytic Hierarchy Binary Model (AHBM) is demonstrated for the justification of WMS. From the extensive analysis of the results, it is found that the WMS is the best among the alternative maintenance systems available.

The Cavender-Felsenstein edge-length invariants for binary characters on 4-trees provide the starting point for the development of "customized" invariants for evaluating and comparing phylogenetic hypotheses. The binary character invariants may be generalized to k-valued characters without losing the quadratic nature of the invariants as functions of the theoretical frequencies f(UVXY) of observable character configurations (U at organism 1, V at 2, etc.). The key to the approach is that certain sets of these configurations constitute events which are probabilistically independent from other such sets, under the symmetric Markov change models studied. By introducing more complex sets of configurations, we find the quadratic invariants for 5-trees in the binary model and for individual edges in 6-trees or, indeed, in any size tree. The same technique allows us to formulate invariants for entire trees, but these are cubic functions for 6-trees and are higher-degree polynomials for larger trees. With k-valued characters and, especially, with large trees, the types of configuration sets (events) used in the simpler examples are too rare (i.e., their predicted frequencies are too low) to be useful, and the construction of meaningful pairs of independent events becomes an important and nontrivial task in designing invariants suited to testing specific hypotheses. In a very natural way, this approach fits in with well-known statistical methodology for contingency tables. We explore use of events such as "only transitions occur for character i (i.e., position i in a nucleic acid sequence) in subtree a" in analyzing a set of data on ribosomal RNA in the context of the controversy over the origins of archaebacteria, eubacteria, and eukaryotes.

Experimental studies have demonstrated that the behavior of real links in low-power wireless networks (such as wireless sensor networks) deviates to a large extent from the ideal binary model used in several simulation studies. In particular, there is a large transitional region in wireless link quality that is characterized by significant levels of unreliability and asymmetry, significantly impacting the performance of higher-layer protocols. We provide a comprehensive analysis of the root causes of unreliability and asymmetry. In particular, we derive expressions for the distribution, expectation, and variance of the packet reception rate as a function of distance, as well as for the location and extent of the transitional region. These expressions incorporate important environmental and radio parameters such as the path loss exponent and shadowing variance of the channel, and the modulation, encoding, and hardware variance of the radios.

To enable content-based functionalities in video coding, a decomposition of the scene into physical objects is required. Such objects are normally not characterised by homogeneous colour, intensity, or optical flow. Therefore, conventional techniques based on these low-level features cannot perform the desired segmentation. The authors address segmentation and tracking of moving objects and present a new video object plane (VOP) segmentation algorithm that extracts semantically meaningful objects. A morphological motion filter detects physical objects by identifying areas that are moving differently from the background. A new filter criterion is introduced that measures the deviation of the estimated local motion from the synthesised global motion. A two-dimensional binary model is derived for the object of interest and tracked throughout the sequence by a Hausdorff object tracker. To accommodate for rotations and changes in shape, the model is updated every frame by a two-stage method that accounts for rigid and non-rigid moving parts of the object. The binary model then guides the actual VOP extraction, whereby a novel boundary post-processor ensures high boundary accuracy. Experimental results demonstrate the performance of the proposed algorithm.

A bivariate binary model is developed for estimating the change in land cover from satellite images obtained at two different times. The binary classifications of a pixel at the two times are modeled as potentially correlated random variables, conditional on the true states of the pixel. The model can be fit to a "training" set of pixels for which the true states are presumed from a reference dataset, and two methods are proposed for using the results of that fit to predict the true states in a separate set of pixels having only classification information. Applied to two images taken over Mexico by the LANDSAT Multi-Spectral Scanner, this methodology finds statistically significant temporal correlation of pixel classifications and illustrates that adjustment for this correlation is important for obtaining accurate estimates of changes in land cover.

The current lack of a classification system for Semantic Data Models (SDMs) is the result of their dependence on standard predicate calculus, which is limited in expressive power. Consequently, many issues in Database Theory cannot adequately be expressed, such as: temporal concepts (before/after insert/update/delete), the triple: true, false, unknown “facts”, existent and non-existent “objects” (null), private and “overlapping” Databases with—potentially—conflicting data, i.e. “possible” and “shared” worlds. The classification framework presented is based on systems of logic with greater expressive power than predicate calculus. In these logics, factual, semantic or intensional, modal, and probabilistic statements can be expressed. Two general classification criteria are established: 1. (a) what can be modelled or expressed in the SDM? 2. (b) what can be derived or deduced in the SDM? The descriptive and classificatory apparatus developed provides a satisfactory framework for representing and explaining the topics above and other theoretical issues, such as “open-world assumption” vs “closed-world assumption”, “null-objects” vs “unknown objects”. The individual features are applied to the analysis and comparison of five Database Models, among them Codd's RM/T and Abrial's binary model. The adequacy of the criteria is further shown by demonstrating that the descriptive features used by Tsichritzis/Lochovsky in Data Models are contained (as a proper subset) in the framework. The paper concludes with an outlook on inductive systems.

In this paper we formalize a ternary model which is being used to study the behavior of binary sequential gate networks. We first describe a binary model which is capable of a detailed description of network behavior, but involves a number of steps that grows exponentially in the number of gates. The complexity of the ternary model is linear in the number of gates;however, only partial information is obtained in generaL A mathematical theory is developed making precise these two models and the comparison between them. A number of examples illustrate these results. This work generalizes previously reported research.

Molecular dynamics calculations have been performed to determine the mutual diffusion coefficient D 12 i.e. the dynamic cross correlations in a binary model mixture. The mean square displacement as well as the velocity-correlation function of the centre of mass of particles of kind 1 have been used for the determination. From various pilot runs it turned out that using runs of a length of 105 time-steps the cross correlations can be very accurately evaluated in terms of D 12/D 12 0, where D 12 0 is the pure mutual diffusion coefficient available through the two self diffusion coefficients of the mixture. Whilst the overall error for this quotient D 12/D 12 0 is found to be 3 per cent, the inaccuracy in D 12 itself is slightly larger because of the additional evaluation of the thermodynamic factor for non-ideal mixtures. Systematic errors have been discovered in earlier molecular dynamics calculations of the D 12, which are primarily due to the use of too short runs. Our calculations resulted in positive c...

The specific retention volume of isooctane, tetrachloromethane and toluene were measured in the Apiezon K-hydogen, nitrogen and carbon dioxide systems at temperatures of 50 and 75 C and at pressure of 10–100 atm for hydrogen and nitrogen and 10–50 atm for carbon dioxide. By comparing the results with the predictions derived from the concept of a pseudo-binary model, it was possible to assess the effect of the carrier gas dissolved in the stationary phase on the specific retention volume. The largest deviations from the pseudo-binary model were found with the isooctane-Apiezon K-carbon dioxide system.

An examination of the existing period searches for 2CG195 + 4 leads to the conclusion that the 59 second periodicity is highly significant only for the 1981 March 17–18 detection of Bignami, Caraveo & Paul (1984). The statistical significance is increased substantially if the pulsation period is half the previously reported value. The period derivative is not well determined. Here we propose that 2CG 195 + 4 is a neutron star powered by accretion from a low (≲ 1M ⊙) mass main-sequence companion. A distance of a few hundred pc would imply that the neutron star is a fast rotator and is spinning down.

A thermodynamic model for quadrilateral pyroxene solutions, is developed from the following assumptions: 1) Non-convergent cation-disorder of Fe and Mg occurs over the Ml and M2 sites; 2) Ca is partitioned completely into the M2 site; and 3) Clinopyroxenes unmix to a high-Ca plus low-Ca phase. This ternary model is an extension of Thompson's (1969, 1970) binary model. Model expressions are presented that describe cation distributions, exchange equilibria and chemical potentials of both ternary and quadrilateral components.

The aim of an effective retrieval system is to yield high recall and precision (retrieval effectiveness). The nonbinary independence model, which takes into consideration the number of occurrences of terms in documents, is introduced. It is shown to be optimal under the assumption that terms are independent. It is verified by experiments to yield significant improvement over the binary independence model. The nonbinary model is extended to normalized vectors and is applicable to more general queries. Various ways to alleviate the consequences of the term independence assumption are discussed. Estimation of parameters required for the nonbinary independence model is provided, taking into consideration that a term may have different meanings.

A model called the binary independence model is presented as a generalization of a few models which have applied to the analyses of a clustered search process, some indexing strategies and a relevance feedback process. This model, together with the Swets model, the linked-2-Poisson model, the 2-Poisson model, the binary limited-dependence model, the tree dependence model, the binary dependence model and the non-binary independent model are compared and contrasted. Despite the fact that these models are intended for different applications, three aspects of modelling are identified, based on which, these models are compared. The three aspects are the class concept, the distribution of similarities and the relation between a matching function and its retrieval effectiveness. As results of the comparison between the models, more insight into the models is gained and a set of guidelines are suggested to help a system designer to choose a model.

If real, Nereid's recently observed large photometric variations (Schaefer and Schaefer, 1988) can be explained by modelling this Neptunian satellite as a quasi-contact binary system made of two similar, ellipsoidal components distorted by their mutual tides. Both the amplitude and the likely periodicity of the observed luminosity changes are consistent with the binary model, provided Nereid's density is close to 1 g cm−3 (similar to that of most outer solar system satellites). The assumed binary would be probably stable against Neptune's gravitational perturbations, and its origin - as already suggested for a few suspected binary asteroids, like 624 Hektor (Weidenschilling, 1980; Farinella et al., 1982) - could be due to rotational fission following a catastrophic impact. During the Neptune encounter due for August, 1989, Voyager 2's cameras will provide images adequate to confirm, or disprove, the binary model.

An iterative general model for psychophysical discrimination, as linear two-factor networks, is proposed. The barriers encountered by the past generalizations of Landahl's binary model for psychophysical discrimination are analyzed. The model proposed here has a built in self-resetting feature. This feature enables the system to carry on various consecutive discrimination processes. Moreover, the model is constructed in such a way that these consecutive discrimination processes do not interfere with each other (the network has no memory). A short analysis is given to the relation and realization of the model as a McCulloch-Pitts neural network.

The effect of assuming independence in the use of Bayes' Theorem for classification and estimation of risk is examined. Analytic results are provided for two specific multivariate normal models and for a model involving binary variables. Monte Carlo results are presented for the former. In these specific cases and an example from medical research, the (false) independence assumption results in classification error rates comparable or better than rates obtained by using the correct model. For a number of covariance structures selected, the a posteriori distribution becomes more U-shaped as the number of variables increases, thus biasing the estimate of risk toward zero or one.

In conventional information retrieval Boolean combinations of index terms are used to formulate the users'' information requests. While any document is in principle retrievable by a Boolean query, the amount of output obtainable by Boolean processing is difficult to control, and the retrieved items are not ranked in any presumed order of importance to the user population. In the vector processing model of retrieval, the retrieved items are easily ranked in decreasing order of the query-record similarity, but the queries themselves are unstructured and expressed as simple sets of weighted index terms. A new, extended Boolean information retrieval system is introduced which is intermediate between the Boolean system of query processing and the vector processing model. The query structure inherent in the Boolean system is preserved, while at the same time weighted terms may be incorporated into both queries and stored documents; the retrieved output can also be ranked in strict similarity order with the user queries. A conventional retrieval system can be modified to make use of the extended system. Laboratory tests indicate that the extended system produces better retrieval output than either the Boolean or the vector processing systems.

The main difficulty in the mathematical simulation of two-phase flows of gas-condensate or gassed oil in reservoirs is connected with a choice of binary or ternary models of hypothetical components representing the real multi-component mixture. The reduction of the number of degrees of freedom is illustrated by a plot of dependence of Gibbs concentration parameter on pressure for some numerical solutions. These solutions are calculated on the basis of balance equations, generalized Darcy law and equilibrium phase composition for a system of methane- n -butane-decane. It is shown that a binary model is adequate for the simulation of steady, quasi-stationary and self-similar flows into a well. Mathematical simulations of well-capacity for steady flows and processes of pressure build-up are considered. The mathematical problem of gas-condensate driven by dry gas is formulated. The corresponding solution with discontinuities is discussed by means of balance laws for jumps. It is shown that in the case of gas cycling processes a ternary model is necessary as the simplest one. The different approaches to the problem are also discussed.

This paper develops a general method for treating discrete data sets containing individuals that have made more than one choice under varying stimuli. The multinomial probit model is shown to possess properties that make it very attractive for this application, as with it, it is possible to develop an estimation process that uses all the information in the data, and is both relatively inexpensive and consistent with utility maximization. The method, which is a generalization of Heckman's binary model, can include taste variations and more than two alternatives.

The previous eccentric-orbit binary model for the recurrent X-ray sources is modified by taking account of the velocity field of the stellar wind. The resultant formula of the light curves for the X-ray sources may have an useful application to the observed X-ray sources.

As a tool to search for short geomagnetic polarity events recorded in the oceanic crust, a new computer algorithm has been devised to model oceanic magnetic anomalies. The main departure of the present approach from earlier analyses is to impose an additional constraint on the model: The blocks representing the magnetic layer all have the same intensity of magnetization except for a binary multiplier of plus or minus unity. This constraint permits the use of blocks with very small widths. Different magnetic profiles can be correlated by simple stacking of models so that real events will reinforce each other. The technique has been applied to the East Pacific Rise with reasonable results.

A model is proposed for describing heat of mixing behavior in binary and ternary metallic solutions. The binary model, which has the form, ΔH M =α1 X 2 X B +α2 X A X 2 −α3 X 2 X 2 , whereX A andX B are mole fractions of componentsA andB and α1, α2, and α3 are constants, is applied to the heat of mixing values for 84 solid and liquid systems and the results are compared with the subregular model. The ternary model, which is composed of the sum of the binary equations and a ternary interaction term of the form α ABC X A X B X C , was applied to the Bi−Cd−Pb, Cd−Pb−Sn, and Cd−Pb−Sb systems. There was excellent agreement both as to the shapes of the isoenthalpy of mixing curves and as to the heat of mixing values in the ternary systems when the model was used to predict the experimental values.

Integration of pathway and protein-protein interaction (PPI) data can provide more information that could lead to new biological insights. PPIs are usually represented by a simple binary model, whereas pathways are represented by more complicated models. We developed a series of rules for transforming protein interactions from pathway to binary model, and the protein interactions from seven pathway databases, including PID, BioCarta, Reactome, NetPath, INOH, SPIKE and KEGG, were transformed based on these rules. These pathway-derived binary protein interactions were integrated with PPIs from other five PPI databases including HPRD, IntAct, BioGRID, MINT and DIP, to develop integrated dataset (named PathPPI). More detailed interaction type and modification information on protein interactions can be preserved in PathPPI than other existing datasets. Comparison analysis results indicate that most of the interaction overlaps values (O AB) among these pathway databases were less than 5%, and these databases must be used conjunctively. The PathPPI data was provided at http://proteomeview.hupo.org.cn/PathPPI/PathPPI.html.

This paper presents a decision supporting tool for the location of electronic toll gantries in freeways, regarding the maximization of the toll revenue. The adopted case study consists in one of the most important Portuguese freeways, with 180 km of extension and a recently introduced electronic toll collection system. In the first stage of the modeling procedure, we applied a categorical binary model to set drivers’ route choice between the tolled freeway segments and the fastest non-tolled alternative paths, based on traffic data collected before and after the introduction of the toll fees. Then, we developed an optimization model to assign a limited or unlimited number of toll gantries to the freeway segments considering the generalized costs of the trips performed using the freeway and the alternative routes. The results showed that charging for all of the freeway segments may not be the best solution to increase road pricing revenue.

Indirect reciprocity is a reputation-based mechanism for cooperation in social dilemma situations when individuals do not repeatedly meet. The conditions under which cooperation based on indirect reciprocity occurs have been examined in great details. Most previous theoretical analysis assumed for mathematical tractability that an individual possesses a binary reputation value, i.e., good or bad, which depends on their past actions and other factors. However, in real situations, reputations of individuals may be multiple valued. Another puzzling discrepancy between the theory and experiments is the status of the so-called image scoring, in which cooperation and defection are judged to be good and bad, respectively, independent of other factors. Such an assessment rule is found in behavioral experiments, whereas it is known to be unstable in theory. In the present study, we fill both gaps by analyzing a trinary reputation model. By an exhaustive search, we identify all the cooperative and stable equilibria composed of a homogeneous population or a heterogeneous population containing two types of players. Some results derived for the trinary reputation model are direct extensions of those for the binary model. However, we find that the trinary model allows cooperation under image scoring under some mild conditions., Comment: 5 figures, 1 table

The hypothesis that a significant fraction of Be stars are interacting binaries is discussed in general terms. The author believes that the observed Be stars are a mixture of three different types of objects. The weakest point of the single-star hypothesis is probably the difficulty in explaining the quasi-periodic V/R variations; the weakest point of the binary hypothesis appears to be the statistical expectancy of a fairly high number of eclipsing systems among them.

X-ray sources referred to as galactic bulge sources generally show no eclipses and no periodic pulsations. However, binary periods in some of them have been discovered. Sco X-1 is the first source of this class with a binary period of 0.787 day (Gottlieb et al, 1975; Cowley and Crampton,1975). The short binary periods of this class of sources are consistent with a model of Joss and Rappaport (1979) wherein the source is a neutron star in a binary system with a very low-mass companion (≲ 0.5 M⊙). A much longer binary period has been discovered for Cyg X-2 (9.843 days) by optical spectroscopic observations (Cowley et al,1979). Such a long binary period is not consistent with the low-mass close binary model of Joss and Rappaport (1979); rather, it suggests that the primary is a somewhat evolved low-mass star (Cowley et at,1979).

Most document retrieval systems based on probabilistic models of feature distributions assume random selection of documents for retrieval. The assumptions of these models are met when documents are randomly selected from the database or when retrieving all available documents. A more suitable model for retrieval of a single document assumes that the best document available is to be retrieved first. Models of document retrieval systems assuming random selection and best-first selection are developed and compared under binary independence and two Poisson independence feature distribution models. Under the best-first model, feature discrimination varies with the number of documents in each relevance class in the database. A weight similar to the Inverse Document Frequency weight and consistent with the best-first model is suggested which does not depend on knowledge of the characteristics of relevant documents.

Cinefluorographic analyses of the articulatory movements of two speakers were used to evaluate a binary model of velar control. To obtain precise timing data for movements of the tongue and velum, radiopaque markers were attached to these structures and then tracked by cinefluorography. It is argued that the binary control model does not survive rigorous empirical test because (1) it makes some predictions that are inappropriate for American English, and (2) the confirmation criteria used in previous reports were applied inconsistently. We suggest that if binary control models are to be used in making predictions about the timing of articulations, then the binary feature values should be interpreted by means of a systematic phonetics or an elaborated speech production model. We further suggest that sequences of articulatory movements may be organized in a hierarchical fashion, such that neuromotor instructions from the motor command system often are issued simultaneously for the tongue, velum, lips, and jaw, even though the commands may not always apply to the same phonetic segment.

Two methods are given to improve weighting schemes by using relevance information of a set of queries. The first method is to estimate parameter values of two independence models in information retrieval — the binary independence model and the non-binary independence model. The parameters estimated here are used to calculate optimal weights for terms in a different set of queries. Performance of this estimation is compared to the inverse document frequency method, the cosine measure, and the statistical similarity measure. The second method is to learn optimal weights of the non-binary independence model adaptively by a learning formula. Experiments are performed on three different document collections CISI, MEDLARS, and CRN4NUL for both methods, and results are reported. Both methods show improvements compared to the existing weighting schemes. Experimental results show that the second method gives slightly better performance than the first one, and has simpler implementation.

Most document retrieval systems based on probabilistic models of feature distributions assume random selection of documents for retrieval. The assumptions of these models are met when documents are randomly selected from the database or when retrieving all available documents. A more suitable model for retrieval of a single document assumes that the best document available is to be retrieved first. Models of document retrieval systems assuming random selection and best-first selection are developed and compared under binary independence and two Poisson independence feature distribution models. Under the best-first model, feature discrimination varies with the number of documents in each relevance class in the database. A weight similar to the Inverse Document Frequency weight and consistent with the best-first model is suggested which does not depend on knowledge of the characteristics of relevant documents.

Probabilistic document retrieval systems consistent with the two Poisson independence model outperforms the binary independence model if the terms are distributed as described by the model's assumptions. The Two Poisson Effectiveness Hypothesis suggests that retrieval models based upon the two Poisson model will outperform binary independent models when used on a “real-world” database, where independence and two Poisson term occurrence distributions fail to hold, because the added information obtained from incorporating term frequency information will more than compensate for the non-Poisson distributions of terms. Searches of the MED1033 database suggest that if terms are not independent and frequencies of term occurrence are not distributed in a two Poisson manner, the binary independence sequential retrieval model outperforms the two Poisson independence retrieval model.

In this paper, I shall present another model for V1329 Cyg. Grygar et al. (1979) proposed a long period eclipsing binary model consisting of a massive M giant and a hot component. Some problems, however, have remained on the binary model. Namely, the mass function is too large, the amplitude of the light variations changes from period to period, the light curve differs from that of Algol type systems and is similar to long period binaries, and so on (iijima et al. 1981). It has been believed that some peculiarities in the system could explain those problems. Recently however, some phenomena which are inconsistent with the binary model were observed (Iijima and Mammano 1981).

The behavior of sequential gate networks can be represented mathematically by using a binary model of gates. Unfortunately, the analysis algorithms in such a model grow exponentially with the number of gates. In this paper we describe an analysis method based on a ternary model of gates, which leads to algorithms that grow linearly with the number of gates.

An information retrieval model, named the Generalized Vector Space Model (GVSM), is extended to handle situations where queries are specified as (extended) Boolean expressions. It is shown that this unified model, unlike currently available alternatives, has the advantage of incorporating term correlations into the retrieval process. The query language extension is attractive in the sense that most of the algebraic properties of the strict Boolean language are still preserved. Although the experimental results for extended Boolean retrieval are not always better than the vector processing method, the developments here are significant in facilitating commercially available retrieval systems to benefit from the vector based methods. The proposed scheme is compared to the p-norm model advanced by Salton and coworkers. An important conclusion is that it is desirable to investigate further extensions that can offer the benefits of both proposals.

AGRAWAL et al.1 present an interesting observation of the variable X-ray source Cygnus XR–1 at energies above 20 keV. This communication points out that their observations may be consistently interpreted in terms of the eclipsing binary model for the source that was originally outlined in an article by myself2 (article 1).